torch、CUDA版本以及其他python包安装,参考wenet官方文档:https://github.com/mobvoi/wenet
根据exp/unified_conformer/train.yaml中的描述补全cmvn_file、checkpoint、dict等关键文件,默认模型为16k采样率数据训练所得。
在正确的环境下直接执行python demo.py,默认执行offline的识别。如要修改为录音解码模式请取消demo.py文件112行注释。
Went online decode demo
torch、CUDA版本以及其他python包安装,参考wenet官方文档:https://github.com/mobvoi/wenet
根据exp/unified_conformer/train.yaml中的描述补全cmvn_file、checkpoint、dict等关键文件,默认模型为16k采样率数据训练所得。
在正确的环境下直接执行python demo.py,默认执行offline的识别。如要修改为录音解码模式请取消demo.py文件112行注释。
您好,我试了您的demo.py 使用aishell 的数据没有任何问题,很棒,但是当我用这个demo识别我自己用手机录的音频时,结果完全不对,这个是是么原因呢。录音是.mp3格式,转成了.wav
请问RuntimeError: Backend "sox" is not one of available backends: ['soundfile'].,这个问题怎么解决的?
您好,我用的wenet官方第一个conformer模型,识别效果很差,在exp/unified conformer下增加了那个模型的global_cmvn、final.pt、lang_char.txt文件,请问还需要改动什么地方吗
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